search for: criterions

Dear Professor Bernhard, Sorry for take your time, but I found something strange that I am not able to explain/understand. Suppose that I compute the ADF test by using the criterion="BIC" to select the lags: summary(CADFtest(y, max.lag.y = 20, type = "drift", criterion="BIC")) Suppose that 2 lags are selected. Next, if I set the lags to 2: summary(CADFtest(y,

Hello: I am a rookie in using R. When I used the unit root test in "CADFtest", I got the different t-test statistics between using criterion="BIC" and no using criterion. But when I checked the result with eviews, I find out that no using criterion is correct. Why after using criterion="BIC", I got the different result? Paul > data(Canada) > ADFt

Hello all, i hope you don't mind my off topic question. i want to use the Akaike criterion for variable selection in a regression model. Does anyone know some basic literature about that topic? Especially I'm interested in answers to the following questions: 1. Has (and if so how has) the criterion to be modified, if i estimate the transformations of the variables too? 2. How is the

Hello, I am using the 'regsubsets' function (from leaps package) to get the best linear models to explain 1 variable from 1 to 5 explanatory variables (exhaustive search). Is there anyone who can tell me on which criterion is based the 'regsubsets' function ? Thank you. samuel Samuel BERTRAND Doctorant Laboratoire de Biomecanique LBM - ENSAM - CNRS UMR 8005

Dear R-help members, I'd like to run a binomial logistic stepwise regression with ten explanatory variables and as many interaction terms as R can handle. I'll come up with the right R command sooner or later, but my real question is whether and how the criterion for the evaluation of the different models can be set to be the probability of the residual deviance in the Chi-Square

Hello all, due to unexplained differences between statistical results from collaborators and our lab that arose in the same large proteomics dataset we reevaluated the t.test() function. Here, we found a weird behaviour that is also reproducible in the following small test dataset: Suppose, we have two vectors with numbers and some missing values that refer to the same individuals and that

Hi There, I'm working on some cluster analyses on a large data-set using hclust with Wards method and Manhattan (city block) distance measures. I've created dendrograms to illustrate the clustering criteria, but would like to create a plot to examine for the classic elbow criterion to use in determining the best number of clusters. Ideally I'd like to plot percent variance explained

Dear all, is there any functions which allow to calculate Student t-criterion using means, their SE and sample size? I've seek for, but bulit-in t-criterion works only with initial sample... Best regards, A.Morkovin

Brian The following (which is new to rw1030) occurs with both Windows 98 & Windows ME. I have not tested behaviour under Unix or Linux, but I expect it is no different. text.rpart() prints unwanted NAs (presumably in the splitting criterion position) on terminal nodes. Criterion <- factor(paste("Leaf", 1:5)) Node <- factor(1:5)

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I'm interested in writing some model selection functions (for linear regression models, as a start), which incorporate the PRESS criterion since it, to my knowledge, is not currently implemented in any available model selection procedure. I thought it would be simplest to build on already existing functions like regsubsets in package leaps. It's easy enough to calculate the PRESS

Dear Rers, is there a way to color counties on a full US map based on a criterion one establishes (i.e., all counties I assign the same number should be the same color)? I explored a bit and looks like the package "maps" might be of help. library(maps) One could get a map of the US: map('usa') One could get countries within a US state: map('county', 'iowa', fill

Dear R users (r-help@r-project.org), The definition of AIC (Akaike information criterion) for normal error models has just been changed. Please refer to the paper below on this matter. Eq.(22) is the new definition. The essential part is RSS(n+q+1)/(n-q-3); it is close to GCV. The paper is temporarily available at the "Papers In Press" place. Kunio Takezawa(2012): A Revision of

sorry for my previus (WRONG) answer, as someone already pointed out a solution could be subset(data, PUNTAR==c("IX49","IX48")) > -----Messaggio originale----- > Da: Guazzetti Stefano > Inviato: venerd?? 23 luglio 2004 15.55 > A: 'Luis Rideau Cruz'; r-help at stat.math.ethz.ch > Oggetto: R: [R] retrieve rows from frame assuming criterion > >

Hello All; I need to run a multiple regression analysis and use Akaike's Information Criterion for model selection. I understand that this command will give the AIC value for specified models: AIC(object, ..., k = 2) with "..." meaning any other optional models for which I would like AIC values. But, how can I specify (in the place of "...") that I want R to

Is there an R implementation of a scheme for automatic smoothing parameter selection with loess, e.g., by minimizing one of the AIC/GCV statistics discussed by Hurvich, Simonoff & Tsai (1998)? Below is a function that calculates the relevant values of AICC, AICC1 and GCV--- I think, because I to guess from the names of the components returned in a loess object. I guess I could use

Hello, I am using the function stepAIC (library MASS) to run a backward elimination on my linear regression. The new model stepAIC calculates contains coefficients that have a Pr(>|t|) value below 0.1, but I'd like to have only coefficients with 0.001 or below. How can I change the stop criterion for stepAIC, so that it is more strict? There is a parameter "steps", but it is

Yes, paraphrasing Murphy I can say of myself: "Nothing seems to be able to stop a stupid thought in its pathway from the brain to the keyboard". :-) Sorry once again and thank for your patience. Stefano > -----Messaggio originale----- > Da: Prof Brian Ripley [mailto:ripley at stats.ox.ac.uk] > Inviato: venerd?? 23 luglio 2004 16.30 > A: Guazzetti Stefano > Cc: Luis

Is there a command to get cluster criterion for the cluster methods? SAS has its criterion, but I prefer to do it in R. If there is not a command is there code to produce criteria to choose the number of clusters? Adrian Katschke Statistics Grad Student University of Nebraska-Lincoln [[alternative HTML version deleted]]

Hi everybody, I was wondering if you can help me about a module. In fact, I'm looking for a package or module about Wilks' lambda criterion in R environment. I didn't find it in R website ( http://cran.cict.fr/web/packages/index.html#available-packages-W or http://search.cpan.org/faq.html). If this module exists, could you show me the command line. Thank you very much for your help,